Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	15,647
2	New Jersey	13,358
3	Massachusetts	9,025
4	Rhode Island	8,137
5	Connecticut	7,769
6	District of Columbia	6,125
7	Louisiana	6,023
8	Delaware	4,861
9	Illinois	4,176
10	Michigan	4,140
11	Pennsylvania	3,766
12	Maryland	3,596
13	South Dakota	2,769
14	Indiana	2,649
15	Colorado	2,640
16	Georgia	2,395
17	Mississippi	2,289
18	Iowa	2,264
19	Nebraska	2,239
20	Washington	1,929
21	Virginia	1,856
22	Nevada	1,640
23	New Mexico	1,626
24	New Hampshire	1,578
25	Florida	1,568
26	Tennessee	1,546
27	Ohio	1,542
28	Kansas	1,472
29	Utah	1,457
30	Alabama	1,441
31	North Dakota	1,400
32	Vermont	1,387
33	California	1,277
34	Missouri	1,256
35	South Carolina	1,183
36	Wisconsin	1,177
37	Arkansas	1,087
38	Kentucky	1,053
39	Arizona	1,050
40	Idaho	1,041
41	Texas	1,002
42	North Carolina	1,001
43	Oklahoma	914
44	Minnesota	910
45	Maine	814
46	Wyoming	717
47	West Virginia	627
48	Oregon	595
49	Alaska	482
50	Puerto Rico	481
51	Hawaii	430
52	Montana	423

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Rhode Island	287
2	New Jersey	280
3	Massachusetts	277
4	New York	212
5	District of Columbia	203
6	Delaware	195
7	Illinois	185
8	Connecticut	159
9	Nebraska	145
10	Iowa	134
11	Maryland	124
12	Pennsylvania	117
13	Michigan	105
14	Kansas	102
15	New Mexico	93
16	Indiana	92
17	Virginia	90
18	Colorado	81
19	Mississippi	80
20	Minnesota	78
21	South Dakota	76
22	Georgia	69
23	Louisiana	66
24	North Dakota	54
25	New Hampshire	50
26	Ohio	48
27	Utah	45
28	California	44
29	Wisconsin	44
30	North Carolina	43
31	Arizona	42
32	Kentucky	41
33	Nevada	37
34	Tennessee	37
35	Washington	36
36	Alabama	35
37	Texas	35
38	South Carolina	31
39	Missouri	29
40	Oklahoma	28
41	Florida	24
42	Arkansas	23
43	Maine	17
44	Puerto Rico	15
45	Idaho	14
46	Wyoming	14
47	Oregon	12
48	West Virginia	8
49	Vermont	5
50	Alaska	4
51	Hawaii	2
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	941
2	New Jersey	813
3	Connecticut	633
4	Massachusetts	516
5	Louisiana	400
6	Michigan	379
7	District of Columbia	317
8	Rhode Island	251
9	Pennsylvania	201
10	Illinois	186
11	Maryland	173
12	Delaware	156
13	Indiana	149
14	Colorado	134
15	Washington	107
16	Georgia	105
17	Mississippi	87
18	Ohio	83
19	Nevada	78
20	Vermont	78
21	Virginia	64
22	Minnesota	60
23	Florida	58
24	New Mexico	58
25	Oklahoma	56
26	Alabama	55
27	Missouri	55
28	Wisconsin	54
29	Kentucky	53
30	California	52
31	New Hampshire	52
32	Iowa	51
33	South Carolina	47
34	Kansas	45
35	Arizona	43
36	Maine	39
37	Nebraska	36
38	North Carolina	36
39	Idaho	35
40	Tennessee	30
41	Texas	28
42	North Dakota	24
43	Oregon	24
44	West Virginia	24
45	Arkansas	20
46	South Dakota	19
47	Puerto Rico	16
48	Montana	14
49	Utah	14
50	Wyoming	12
51	Hawaii	11
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	44
2	Massachusetts	27
3	Connecticut	22
4	District of Columbia	18
5	New York	17
6	Pennsylvania	16
7	Michigan	12
8	Louisiana	11
9	Maryland	10
10	Rhode Island	10
11	Delaware	9
12	Illinois	9
13	Indiana	8
14	Ohio	6
15	Colorado	4
16	Georgia	4
17	South Carolina	4
18	Iowa	3
19	Minnesota	3
20	Mississippi	3
21	New Mexico	3
22	Virginia	3
23	Alabama	2
24	California	2
25	Florida	2
26	Missouri	2
27	Nebraska	2
28	Nevada	2
29	New Hampshire	2
30	Oklahoma	2
31	South Dakota	2
32	Washington	2
33	Wisconsin	2
34	Arizona	1
35	Arkansas	1
36	Kentucky	1
37	North Carolina	1
38	Texas	1
39	Vermont	1
40	West Virginia	1
41	Alaska	0
42	Hawaii	0
43	Idaho	0
44	Kansas	0
45	Maine	0
46	Montana	0
47	North Dakota	0
48	Oregon	0
49	Puerto Rico	0
50	Tennessee	0
51	Utah	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	102,836	1	99
Lincoln	Arkansas	62,500	2	99
Bledsoe	Tennessee	39,432	3	99
Rockland	New York	35,937	4	99
Dakota	Nebraska	35,154	5	99
Davidson	Tennessee	3,845	220	92
Richland	South Carolina	2,162	463	85
Pierce	Washington	1,587	666	78
Orange	California	762	1252	60
York	South Carolina	747	1276	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,683	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	2,227	3	99
Early	Georgia	1,963	4	99
Nassau	New York	1,556	5	99
Richland	South Carolina	79	548	82
Pierce	Washington	56	707	77
Davidson	Tennessee	40	870	72
Orange	California	14	1278	59
York	South Carolina	11	1328	57

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.